{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2 Physical GPUs, 2 Logical GPUs\n"
     ]
    }
   ],
   "source": [
    "import torch\n",
    "import graphgallery \n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "\n",
    "# Set if memory growth should be enabled for ALL `PhysicalDevice`.\n",
    "graphgallery.set_memory_growth()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'1.6.0+cu101'"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "torch.__version__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'0.4.0'"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "graphgallery.__version__"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Load the Datasets\n",
    "+ cora\n",
    "+ citeseer\n",
    "+ pubmed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "from graphgallery.data import Planetoid\n",
    "\n",
    "# set `verbose=False` to avoid these printed tables\n",
    "data = Planetoid('cora', root=\"~/GraphData/datasets/\", verbose=False)\n",
    "graph = data.graph\n",
    "idx_train, idx_val, idx_test = data.split()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'citeseer', 'cora', 'pubmed'}"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.supported_datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "PyTorch 1.6.0+cu101 Backend"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "graphgallery.set_backend(\"pytorch\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training...\n",
      "100/100 [==============================] - 0s 2ms/step - loss: 0.7679 - acc: 0.9143 - val_loss: 1.1458 - val_acc: 0.7780 - time: 0.1659\n",
      "Testing...\n",
      "1/1 [==============================] - 0s 439us/step - test_loss: 1.1232 - test_acc: 0.8270 - time: 4.3161e-04\n",
      "Test loss 1.1232, Test accuracy 82.70%\n"
     ]
    }
   ],
   "source": [
    "from graphgallery.nn.models import SGC\n",
    "model = SGC(graph, attr_transform=\"normalize_attr\", device='GPU', seed=123)\n",
    "model.build()\n",
    "# train with validation\n",
    "his = model.train(idx_train, idx_val, verbose=1, epochs=100)\n",
    "# train without validation\n",
    "# his = model.train(idx_train, verbose=1, epochs=100)\n",
    "loss, accuracy = model.test(idx_test)\n",
    "print(f'Test loss {loss:.5}, Test accuracy {accuracy:.2%}')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualization Training "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "with plt.style.context(['science', 'no-latex']):\n",
    "    fig, axes = plt.subplots(1, 2, figsize=(15, 5))\n",
    "    axes[0].plot(his.history['acc'], label='Train accuracy')\n",
    "    axes[0].plot(his.history['val_acc'], label='Val accuracy')\n",
    "    axes[0].legend()\n",
    "    axes[0].set_title('Accuracy')\n",
    "    axes[0].set_xlabel('Epochs')\n",
    "    axes[0].set_ylabel('Accuracy')\n",
    "\n",
    "\n",
    "    axes[1].plot(his.history['loss'], label='Training loss')\n",
    "    axes[1].plot(his.history['val_loss'], label='Validation loss')\n",
    "    axes[1].legend()\n",
    "    axes[1].set_title('Loss')\n",
    "    axes[1].set_xlabel('Epochs')\n",
    "    axes[1].set_ylabel('Loss')\n",
    "    \n",
    "    plt.autoscale(tight=True)\n",
    "    plt.show()    "
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
